def build_model(class_num):
model = layer.Sequential()
model.add(layer.Reshape([1, 28, 28]))
model.add(layer.SpatialConvolution(1, 6, 5, 5))
model.add(layer.Tanh())
model.add(layer.SpatialMaxPooling(2, 2, 2, 2))
model.add(layer.Tanh())
model.add(layer.SpatialConvolution(6, 12, 5, 5))
model.add(layer.SpatialMaxPooling(2, 2, 2, 2))
model.add(layer.Reshape([12 * 4 * 4]))
model.add(layer.Linear(12 * 4 * 4, 100))
model.add(layer.Tanh())
model.add(layer.Linear(100, class_num))
model.add(layer.LogSoftMax())
return model
def get_activation_by_name(activation_name, activation_id=None):
""" Convert to a bigdl activation layer
given the name of the activation as a string """
import bigdl.nn.layer as BLayer
activation = None
activation_name = activation_name.lower()
if activation_name == "tanh":
activation = BLayer.Tanh()
elif activation_name == "sigmoid":
activation = BLayer.Sigmoid()
elif activation_name == "hard_sigmoid":
activation = BLayer.HardSigmoid()
elif activation_name == "relu":
activation = BLayer.ReLU()
elif activation_name == "softmax":
activation = BLayer.SoftMax()
elif activation_name == "softplus":
activation = BLayer.SoftPlus(beta=1.0)
elif activation_name == "softsign":
activation = BLayer.SoftSign()
elif activation_name == "linear":
activation = BLayer.Identity()
else:
raise Exception("Unsupported activation type: %s" % activation_name)
if not activation_id:
activation.set_name(activation_id)
return activation
def to_bigdl_activation(self, activation_name, activation_id):
activation = None
if activation_name == "tanh":
activation = BLayer.Tanh()
elif activation_name == "sigmoid":
activation = BLayer.Sigmoid()
elif activation_name == "relu":
activation = BLayer.ReLU()
elif activation_name == "softmax":
activation = BLayer.SoftMax()
else:
raise Exception("Unsupported activation type: %s" %
activation_name)
activation.set_name(activation_id)
return activation
